Cancer drug development has undergone massive changes during the past decade, largely as a result of targeted therapies that have stemmed from increased understanding of the molecular aspects of cancer. Moreover, we can now assess the molecular driving forces behind each patient's cancer, offering possibilities for individually tailored therapies. Despite advances in the pace of molecular target identification and drug discovery, translation to safe and effective therapies remains challenging. Rates of attrition in cancer drug development are alarmingly high with estimates that at least 80% of oncology drugs entering Phase I clinical trials will not make it to market (Walker et al., Nat. Rev. Drug Discov. 8:15-16, 2009). Consequently, the cost of drug development is skyrocketing and a recent analysis set the price of bringing a new drug to market at $0.8-1.0 billion (Walker et al., Nat. Rev. Drug Discov. 8:15-16, 2009). To address these issues, experts and regulatory agencies have called for increased use of biomarkers in cancer drug development (Workman et al., Cancer Res. 98:580-598, 2006; Khleif et al., Clin. Cancer Res. 16:3299-3318, 2010). Arguably, the most useful type of biomarker for drug development will be one that predicts for response to a drug because it will allow patients to be pre-selected for clinical trials. This should increase the chances of observing a clinical response and thereby reduce the number of patients who need to take part in the trial. Examples of validated predictive biomarkers include HER2 levels to predict response to trastuzumab for breast cancer patients, EGFR mutations that predict response to small molecule EGFR inhibitors in lung cancer, and K-Ras mutations as a contraindication to therapy with EGFR inhibitors in the setting of colon cancer (Linardou et al., Lancet Oncol. 9:962-672, 2008). In some cases, the biomarker is the molecular target of the drug, as with HER2. In others, the relationship is indirect—e.g. the increased sensitivity of patients with BRCA mutations to PARP inhibitors due to a “synthetic lethal” effect (Annunziata et al., Biol Rep. 2, p. 10, 2010)—or based on purely empirical observations.
Prostate cancer will claim the lives of more than 30,000 American men this year (American Cancer Society Facts and Figures 2010). African American men will be disproportionately represented in this group, being more than twice as likely to die from prostate cancer compared to Caucasian American men (American Cancer Society Facts and Figures 2010). Men who present with localized prostate cancer have an excellent chance for a cure following treatment by surgery and/or radiotherapy, although these treatments can have significant side effects. Men who have regionally advanced or metastic disease at the time of diagnosis often have long-term cancer control when treated by androgen-deprivation therapies (ADT), but cures are rare because the disease inevitably becomes resistant to therapy and progresses to castration-resistant prostate cancer (CRPC). CRPC causes considerable morbidity, notably bone pain and fatigue, and survival is typically 1-3 years. Treatment options for patients with CRPC are limited because the disease is generally resistant to chemotherapies. Docetaxel can produce a modest increase in median survival, but almost all patients will eventually progress. Therefore, there is a clear need in the art for novel therapies that can effectively treat CRPC.
Extensive basic/translational research has revealed many of the biological changes associated with progression to CRPC, by both androgen receptor (AR)-dependent and AR-independent pathways (Bonkhoff et al., Prostate 70:100-112, 2010). It is clear that CRPC is a heterogenous disease, so it is unlikely that a “one size fits all” therapy can be developed. However, several pathways have emerged that are frequently upregulated in advanced prostate cancers and these represent targets for development of therapies that should help the majority of men with this disease.
Therefore, what is needed then are markers for identifying patients suffering from prostate and other cancers which can be used to predict the therapeutic efficacy of agents used to treat the disease.